Systems and methods for triggering an out of focus alert

ABSTRACT

In order to trigger an out of focus alert when the focus level of a video frame meets a focus criteria, a method is performed including the operations of: receiving a video frame, partitioning the video frame into a plurality of blocks, calculating an array of discrete cosign transformation (DCT) coefficients for at least one of the plurality of blocks using a DCT, classifying each of the at least one of the plurality of blocks based on the array of DCT coefficients for that block, calculating a focus level of the video frame from the block classifications, and triggering an out of focus alert if the focus level meets a focus criteria.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority pursuant to 35 U.S.C. §119(e) toU.S. Provisional Application Ser. No. 60/952,896 entitled, “VideoProcessing,” filed on Jul. 31, 2007, which is hereby incorporated byreference in its entirety. The present application is also acontinuation of and claims priority to U.S. patent application Ser. No.11/937,553, filed on Nov. 9, 2007 entitled SYSTEMS AND METHODS FORTRIGGERING AN OUT OF FOCUS ALERT, which is hereby incorporated byreference in its entirety.

TECHNICAL FIELD

This disclosure is related to the field of video imaging, and inparticular, to the automatic triggering of an alert when a video frameis determined to be out of focus.

BACKGROUND

Currently video cameras are used for a variety of purposes, includingsecurity cameras, data collection, web cameras, and many other uses.Often, a video camera will be configured to continually capture videodata without much if any interaction with a user. However, it ispossible for the camera to lose its focus due to a variety of reasons.In such a case, the out of focus camera may not be recognized for aperiod of time.

SUMMARY

In this regard, systems and methods for triggering an out of focus alertare provided. An exemplary embodiment of such a method comprisesreceiving a video frame, partitioning the video frame into a pluralityof blocks, calculating an array of discrete cosign transformation (DCT)coefficients for at least one of the plurality of blocks using a DCT,classifying each of the at least one of the plurality of blocks based onthe array of DCT coefficients for that block, calculating a focus levelof the video frame from the block classifications, and triggering an outof focus alert if the focus level meets a focus criteria.

An exemplary embodiment of a system comprises a storage systemcontaining software, and a processing system coupled to the storagesystem. The processing system is instructed by the software to receive avideo frame, partition the video frame into a plurality of blocks,calculate an array of discrete cosign transformation (DCT) coefficientsfor at least one of the plurality of blocks using a DCT, classify eachof the at least one of the plurality of blocks based on the array of DCTcoefficients for that block, calculate a focus level of the video framefrom the block classifications, and trigger an out of focus alert if thefocus level meets a focus criteria.

An exemplary embodiment of a computer-readable medium of instructionsfor triggering an out of focus alert in a computer system comprisesreceiving a video frame, partitioning the video frame into a pluralityof blocks, calculating an array of discrete cosign transformation (DCT)coefficients for at least one of the plurality of blocks using a DCT,classifying each of the at least one of the plurality of blocks based onthe array of DCT coefficients for that block, calculating a focus levelof the video frame from the block classifications, and triggering an outof focus alert if the focus level meets a focus criteria.

Other systems, methods, features and/or advantages of this disclosurewill be or may become apparent to one with skill in the art uponexamination of the following drawings and detailed description. It isintended that all such additional systems, methods, features and/oradvantages be included within this description and be within the scopeof the present disclosure

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the disclosure can be better understood with referenceto the following drawings. The components in the drawings are notnecessarily to scale, emphasis instead being placed upon clearlyillustrating the principles of the present disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views. While several embodiments are described inconnection with these drawings, there is no intent to limit thedisclosure to the embodiment or embodiments disclosed herein. On thecontrary, the intent is to cover all alternatives, modifications, andequivalents.

FIG. 1 is a flowchart illustrating a method for triggering an alertaccording to an embodiment of the invention;

FIG. 2 is an illustration of the structure of an array of discretecosign transformation coefficients according to an embodiment of theinvention;

FIG. 3 is an illustration of the structure of a weight array accordingto an embodiment of the invention;

FIG. 4 is block diagram of a video system according to an embodiment ofthe invention;

FIG. 5 is an illustration of a mask according to an embodiment of theinvention;

FIG. 6 is a flowchart illustrating a method for triggering an alertaccording to an embodiment of the invention;

FIG. 7 is a flowchart illustrating a method for classifying blocksaccording to an embodiment of the invention; and

FIG. 8 is a block diagram illustrating a computer system in anembodiment of the invention.

DETAILED DESCRIPTION

As discussed above, video cameras may go out of focus for a wide varietyof reasons, including tampering. In order to alert a user when a cameragoes out of focus, a method for monitoring the focus level of a videocamera, and automatically triggering an alert when the focus level meetsa focus criteria is presented. While some current cameras have theability to auto-focus, this feature is not perfect. For example, thecamera may focus on an object at a different distance from the camera,other than the object of interest in the video frame. For a wide varietyof reasons, it may be desired to configure a video camera for manualfocus on a particular area of interest. Unless this camera iscontinually monitored, it is possible for the camera to go out of focuswithout being observed. By measuring the focus level of a video frame,and comparing this focus level to a criteria, an apparatus or method isconfigured to trigger an alert when the focus level is reduced to alevel meeting the criteria.

FIG. 1 is a flowchart illustrating a method for triggering an alertaccording to an embodiment of the invention. In operation 100, a videoframe is received. In operation 102, the video frame is partitioned intoa plurality of blocks. In some example embodiments, the video frame maybe partitioned into 8 pixel by 8 pixel blocks, while other embodimentsmay use other block sizes and shapes all within the scope of the presentinvention. In operation 104, an array of discrete cosign transform (DCT)coefficients are calculated for at least one of the plurality of blocksusing a discrete cosign transform. In an example embodiment, a type-IIDCT is used to calculate the array of DCT coefficients, while otherembodiments may use other types of discrete cosign transforms, allwithin the scope of the present invention. Also, those of skill in theart will note that this method does not require the calculation of DCTcoefficients for all of the blocks in the video image. For a variety ofreasons, one or more of the blocks may be masked such that it does notenter into the focus calculations, all within the scope of the presentinvention. Masking will be discussed in detail below, with respect toFIG. 5.

In operation 106, the at least one of the plurality of blocks isclassified into one of a number of different block types based on thearrays of DCT coefficients for each block. These block types and anexample method of classification will be discussed in detail below, withrespect to FIG. 7. In operation 108, a focus level is calculated for thevideo frame based on the block classifications. In operation 110, analert is triggered if the focus level meets a criteria. Calculation ofthe focus level and the criteria are discussed in detail below, withrespect to FIGS. 6 and 7.

FIG. 2 is an illustration of the structure of an array of discretecosign transformation coefficients according to an embodiment of theinvention. A two-dimensional type-II DCT applied to a block of pixelsmay result in an 8×8 transform coefficient array. Some exampleembodiments may structure this data as a two-dimensional 8×8 array,while other embodiments may structure this data as a one-dimensional 64element array, all within the scope of the present invention. Theexample embodiment described here organizes the DCT coefficient datainto a one-dimensional 64-element array as illustrated in FIG. 2. Thedetailed calculations necessary to perform a discrete cosign transformare known to those of skill in the art and may be found in a number ofreference works, and so are not described in detail herein. FIG. 2 showsa typical 8×8 DCT coefficient array 200 with an origin in the top-leftcorner at array element 0 202. Each entry in this DCT coefficient array200 contains the strength of a different frequency component in the DCT.Entries in the array increase in horizontal and vertical spatialfrequencies as they are found further to the right (horizontal) and down(vertical) from the origin. In this example embodiment a 64-elementarray, dct[0:63], is shown mapped onto the typical 8×8 DCT coefficientarray. dct[0] 202 is the first element in the array and represents theDC (zero-frequency) component of the array. dct[63] 204 is the lastelement in the array, and represents the element with the highesthorizontal and vertical spatial frequencies. The remaining arrayelements are organized as shown in FIG. 2. Notice that array elementswith lower indexes in the array represent lower spatial frequencies,while array elements with higher indexes in the array representrelatively higher spatial frequencies.

FIG. 3 is an illustration of the structure of a weight array accordingto an embodiment of the invention. This 64-element weight array followsthe same structure as the array of DCT coefficients 200 shown in FIG. 2.For example, weight[0] 302 has a value of 1, and weight[63] 304 has avalue of 128 in this example embodiment. Since higher frequencycomponents of the array of DCT coefficients 200 are usually small inmagnitude, some embodiments of the present invention weight the array ofDCT coefficients 200 by a weight array 300, such as that shown in FIG.3. In this example embodiment, the DC coefficient (dc[0]) 202 ismultiplied by a weight (weight[0]) 302 of 1, and so remains unchanged.The coefficient with the highest spatial frequencies (dct[63]) 204 ismultiplied by a weight (weight[63]) 304 of 128. Other embodiments mayuse other weight multipliers (or none at all) within the scope of thepresent invention.

FIG. 4 is block diagram of a video system according to an embodiment ofthe invention. In this example embodiment, a video camera 400 is coupledto a video processor 402, which in turn is coupled to a display 404. Thevideo camera 400 is configured to send a series of video frames to thevideo processor 402. The video processor 402 receives video frames fromthe video camera 400, processes the video frames to determine the focuslevel of one or more of the video frames, and if the focus level meets acriteria, triggers an alert to the display 404, or otherwise alerts theuser to the problem. Those of skill in the art will recognize that thereare a very wide variety of video cameras and displays on the market,many of which may be configured to operate with the video processor 402described herein, all within the scope of the present invention. Also,this video processor 402 may include any mix of hardware and softwareconfigured to operate in the methods described herein, all within thescope of the present invention. For example, the video processor 402 mayinclude a general purpose computer configured to execute the operationsof the methods described herein, while other examples may use videoprocessors specifically designed for this purpose. One example computersystem configured to act as a video processor 402 is described in detailbelow, with respect to FIG. 8.

FIG. 5 is an illustration of a mask according to an embodiment of theinvention. In some situations, the video frames received from a videocamera 400 may include elements that are not useful to a focus levelcalculation. In these situations, it may be desirable to mask outportions of the frame such that these masked areas are not included inthe focus level calculation. Those of skill in the art will recognizethat there are a very wide variety of methods available to mask outportions of a video frame, all within the scope of the presentinvention. For example, some embodiments may mask pixels within thevideo frame on a pixel-by-pixel basis. These masked pixels may beconverted to a uniform mask color (such as black) so that they are notclassified as sharp or unsharp in the block classification step. Stillother embodiments, such as that shown in FIG. 5, mask out portions ofthe video frame on a block-by-block basis. In this example embodiment,an array of 9×8 blocks 500 is shown. These blocks may contain any numberof pixels within the scope of the present invention. In this example, anumber of blocks to be masked 502 from the focus level calculations aremarked with an “X” while blocks to be used 504 in the focus levelcalculations are not marked. Those of skill in the art will recognizethat there are a very wide variety of methods available to encode maskdata, all within the scope of the present invention. In this exampleembodiment, a Mask_String 506 is created to represent the mask data in astring format. In this example, the Mask_String 506 includes asemi-colon separated series of number pairs. Each pair of numbersincludes a number of masked blocks and then a number of unmasked blocks.The string is generated from the mask array 500 by examining the blocksin a left-to-right, top-to-bottom order. In this example, the initialblock (in the upper left corner) is unmasked, so the first number pairis “0;1” representing no initial masked block, and the single initialunmasked block. The next number pair is “2;7” representing the twomasked blocks in the top row followed by seven unmasked blocks. Thisexample method continues in this manner to the end of the mask array,resulting in a final Mask_String 506 of“0;1;2;7;2;7;2;7;2;7;2;7;2;6;3;4;5;4;2.” This Mask_String 506 may thenbe used to determine which blocks will have a DCT run on them, savingcomputing time since masked blocks to not need to be examined and arenot used in the focus level calculations.

FIG. 6 is a flowchart illustrating a method for triggering an alertaccording to an embodiment of the invention. In operation 600, a videoframe is received. In operation 602, the video frame is masked asdescribed above, with respect to FIG. 5. In operation 604, the luminanceof the video frame is scaled. The luminance of the video frame may bescaled such that the method of measuring focus level is less sensitiveto the light condition. In this example, the dynamic range of theluminance is normalized to values from 0 to 255. The maximum intensityof any pixel in the frame is represented by max Int, while the minimumintensity of any pixel in the frame is represented by min Int. Aluminance scalar, α, is calculated as follows:

$\alpha = {\frac{255}{\left\lbrack {{\max\mspace{14mu}{Int}} - \left( {{\min\mspace{14mu}{Int}} + 1} \right)} \right\rbrack}.}$The intensity of each pixel is then scaled by α as follows:Int=α*(Int−minInt).Other embodiments may scale the luminance in other ways, or may notscale the luminance at all, all within the scope of the presentinvention.

In operation 606, the video frame is partitioned into a plurality ofnon-overlapping blocks. In some example embodiments, the video frame maybe partitioned into 8 pixel by 8 pixel blocks, while other embodimentsmay use other block sizes and shapes all within the scope of the presentinvention. In this example, the video frame block size matches the maskblock size so that masked blocks are not processed. In operation 608, anarray of discrete cosign transform (DCT) coefficients are calculated forat least one of the plurality of blocks using a discrete cosigntransform. DCT coefficients are not calculated for masked blocks. In anexample embodiment, a type-II DCT is used to calculate the array of DCTcoefficients while other embodiments may use other types of discretecosign transforms all within the scope of the present invention.

In operation 610, the array of DCT coefficients is weighted by thecontents of a weight array, such as the array illustrated in FIG. 3 anddescribed above. This weighting increases the influence of the higherspatial frequency components of the array of DCT coefficients, sincethese components tend to be very small, and normally would have littleeffect on focus level calculations. Those of skill in the art willrecognize that there are a very wide variety of methods available toweight the array of DCT coefficients, all within the scope of thepresent invention. In operation 612, each of the at least one of theplurality of blocks that have been transformed, are classified into oneof five different block types based on the arrays of DCT coefficientsfor each block. These five block types and an example method ofclassification will be discussed in detail below, with respect to FIG.7. In operation 614, a focus level is calculated for the video framebased on the block classifications. The focus level is set equal to thenumber of sharp blocks divided by the sum of the number of sharp blocksand unsharp blocks. In operation 616, a focus threshold is received.This focus threshold may be pre-programmed, or may be obtained from auser. In operation 618, an alert is triggered if the focus level is lessthan the focus threshold, and has been less than the focus threshold fora set number of frames. The number for consecutive frames requiredbefore triggering an alert may be a fixed quantity, or may be set by auser. This quantity of frames is called a persistence level. Forexample, if the persistence level is set to five frames, then fiveconsecutive out of focus frames must be detected before the alert istriggered. Those of skill in the art will recognize that there are awide variety of methods available to alert a user of an out of focusevent, such as displaying an alert on a display, sounding a tone, orflashing a light, all within the scope of the present invention.

FIG. 7 is a flowchart illustrating a method for classifying blocksaccording to an embodiment of the invention. This example method forclassifying blocks is performed on each unmasked block. In this method,blocks are classified as one of five different block types: dark, noisy,plain, unsharp, or sharp. Those of skill in the art will recognize thatthere are a wide variety of different classifications available, and awide variety of methods for determining these classifications, allwithin the scope of the present invention. For example, some embodimentsmay simply lump together the dark, noisy, and plain blocks into a singleclassification since these blocks are not used in calculating a focuslevel. Other embodiments may include other block types. In this exampleembodiment, in an operation 700, a dark_value, a noise_value, a scalar,a lowScore, and a highScore are calculated from the array of DCTcoefficients for the current block. In all of the followingcalculations, dct[0:63] represents the array of DCT coefficients for thecurrent block, as shown in FIG. 2. The dark_value is set equal todct[0], the DC coefficient. The noise_value is calculated using thefollowing formula:

${noise\_ value} = {\frac{\sum\limits_{k = 0}^{9}{{dct}\lbrack k\rbrack}}{\sum\limits_{k = 48}^{63}{{dct}\lbrack k\rbrack}}.}$The scalar is calculated using the following formula:

${scalar} = {{\min\left( {16,{{\sum\limits_{k = 48}^{63}{{dct}\lbrack k\rbrack}} + 2}} \right)}.}$The lowScore is calculated using the following formula:

${lowScore} = {\left( {\sum\limits_{k = 1}^{5}\left\lbrack \frac{{{dct}\lbrack k\rbrack}*{{weight}\lbrack k\rbrack}}{scalar} \right\rbrack} \right)*{{scalar}.}}$The highScore is calculated using the following formula:

${highScore} = {\left( {\sum\limits_{k = 6}^{63}\left\lbrack \frac{{{dct}\lbrack k\rbrack}*{{weight}\lbrack k\rbrack}}{scalar} \right\rbrack} \right)*{{scalar}.}}$

In an operation 702, the dark_value is compared to a dark threshold. Ifthe dark_value is less than the dark threshold, the block is classifiedas a dark block in operation 704. and the classification of the presentblock is completed 720. If the dark_value is greater than or equal tothe dark threshold, in an operation 706, the noise_value is compared toa noise threshold. If the noise_value is less than the noise threshold,the block is classified as a noisy block in operation 708, and theclassification of the present block is completed 720. If the noise_valueis greater than or equal to the noise threshold, in an operation 710,the lowScore is compared to a plain threshold. If the lowScore is lessthan the plain threshold, the block is classified as a plain block inoperation 712, and the classification of the present block is completed720. If the lowScore is greater than or equal to the plain threshold, inan operation 714, the lowScore is compared to the highScore. If thelowScore is less than the highScore, the block is classified as anunsharp block in operation 716, and the classification of the presentblock is completed 720. If the lowScore is greater than or equal to thehighScore, the block is classified as a sharp block in operation 718,and the classification of the present block is completed 720.

FIG. 8 is a block diagram illustrating a computer system in anembodiment of the invention. Computer system 800 includes communicationinterface 801, processing system 802, and user interface 803. Processingsystem 802 includes storage system 804. Storage system 804 storessoftware 805. Processing system 802 is linked to communication interface801 and user interface 803. Computer system 800 could be comprised of aprogrammed general-purpose computer, although those skilled in the artwill appreciate that programmable or special purpose circuitry andequipment may be used. Computer system 800 may be distributed amongmultiple devices that together comprise elements 801-805.

Communication interface 801 could comprise a network interface, modem,port, transceiver, or some other communication device. Communicationinterface 801 may be distributed among multiple communication devices.Processing system 802 could comprise a computer microprocessor, logiccircuit, or some other processing device. Processing system 802 may bedistributed among multiple processing devices. User interface 803 couldcomprise a keyboard, mouse, voice recognition interface, microphone andspeakers, graphical display, touch screen, or some other type of userdevice. User interface 803 may be distributed among multiple userdevices. Storage system 804 could comprise a disk, tape, integratedcircuit, server, or some other memory device. Storage system 804 may bedistributed among multiple memory devices. The memory can include anyone or combination of volatile memory elements (e.g., random accessmemory (RAM, such as DRAM, SRAM, SDRAM, etc.)) and nonvolatile memoryelements (e.g., ROM, hard drive, tape, CDROM, etc.). Moreover, thememory may incorporate electronic, magnetic, optical, and/or other typesof storage media. Note that the memory can have a distributedarchitecture, where various components are situated remote from oneanother, but can be accessed by the processor. Additionally, the memoryincludes an operating system, as well as instructions associated withmethods for image processing. Exemplary embodiments of each of which aredescribed above.

Processing system 802 retrieves and executes software 805 from storagesystem 804. Software 805 may comprise an operating system, utilities,drivers, networking software, and other software typically loaded onto acomputer system. Software 805 could comprise an application program,firmware, or some other form of machine-readable processinginstructions. When executed by processing system 802, software 805directs processing system 802 to operate as described herein. In thisexample embodiment of the present invention, the software 805 may beconfigured to cause the processing system 802 to execute the operationsof the methods illustrated in FIGS. 1 through 7. The storage system 804may be configured to store the video frame, array of DCT coefficients,weight array, and results of the methods illustrated in FIGS. 1 through7, such as the classification of the blocks, and the various thresholdsdescribed above. In such a configuration, the computer system 800 isacting as the video processor 402 shown in FIG. 4.

One should note that the flowcharts included herein show thearchitecture, functionality, and/or operation of a possibleimplementation of software. In this regard, each block can beinterpreted to represent a module, segment, or portion of code, whichcomprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that in somealternative implementations, the functions noted in the blocks may occurout of the order. For example, two blocks shown in succession may infact be executed substantially concurrently or the blocks may sometimesbe executed in the reverse order, depending upon the functionalityinvolved.

One should note that any of the programs listed herein, which caninclude an ordered listing of executable instructions for implementinglogical functions (such as depicted in the flowcharts), can be embodiedin any computer-readable medium for use by or in connection with aninstruction execution system, apparatus, or device, such as acomputer-based system, processor-containing system, or other system thatcan fetch the instructions from the instruction execution system,apparatus, or device and execute the instructions. In the context ofthis document, a “computer-readable medium” can be any means that cancontain, store, communicate, propagate, or transport the program for useby or in connection with the instruction execution system, apparatus, ordevice. The computer readable medium can be, for example but not limitedto, an electronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device. More specific examples (anonexhaustive list) of the computer-readable medium could include anelectrical connection (electronic) having one or more wires, a portablecomputer diskette (magnetic), a random access memory (RAM) (electronic),a read-only memory (ROM) (electronic), an erasable programmableread-only memory (EPROM or Flash memory) (electronic), an optical fiber(optical), and a portable compact disc read-only memory (CDROM)(optical). In addition, the scope of the certain embodiments of thisdisclosure can include embodying the functionality described in logicembodied in hardware or software-configured mediums.

It should be emphasized that the above-described embodiments are merelypossible examples of implementations, merely set forth for a clearunderstanding of the principles of this disclosure. Many variations andmodifications may be made to the above-described embodiments withoutdeparting substantially from the spirit and principles of thedisclosure. All such modifications and variations are intended to beincluded herein within the scope of this disclosure.

The above description and associated figures teach the best mode of theinvention. The following claims specify the scope of the invention. Notethat some aspects of the best mode may not fall within the scope of theinvention as specified by the claims. Those skilled in the art willappreciate that the features described above can be combined in variousways to form multiple variations of the invention. As a result, theinvention is not limited to the specific embodiments described above,but only by the following claims and their equivalents.

What is claimed is:
 1. A computer system, comprising: a storage systemcontaining software; and a processing system coupled to the storagesystem; wherein the processing system is instructed by the software to:receive a video frame; bias the luminance of the video frame; partitionthe video frame into a plurality of blocks; calculate an array ofdiscrete cosine transformation (DCT) coefficients for at least one ofthe plurality of blocks using a DCT; generate block classifications byclassifying at least one block of the at least one of the plurality ofblocks as noisy based on the array of DCT coefficients for that block;calculate a focus level of the video frame based at least in part on theblock classifications; and trigger an out of focus alert if the focuslevel meets a focus criteria.
 2. The computer system of claim 1, whereineach block is classified as one block type from the group of block typesconsisting of: dark, noisy, plain, unsharp, or sharp.
 3. The computersystem of claim 1, wherein the focus level is calculated by dividing thenumber of sharp blocks by the sum of the number of unsharp blocks andsharp blocks.
 4. The computer system of claim 1, wherein the focuscriteria is a focus threshold.
 5. The computer system of claim 1,wherein the focus criteria includes a persistence level.
 6. The computersystem of claim 1, wherein the array of DCT coefficients for a blockcomprises 64 coefficients.
 7. The computer system of claim 6, whereinthe processing system is further instructed by the software to:calculate a dark value for the block; and classify the block as a darkblock if the dark value is less than a dark threshold.
 8. The computersystem of claim 7, wherein the dark value is equal to dct[0], andwherein dct[0:63] is the array of DCT coefficients, and dct[0] is thefirst element in the array of DCT coefficients.
 9. The computer systemof claim 8, wherein the noise is equal to$\frac{\sum\limits_{k = 0}^{0}{{dct}\lbrack k\rbrack}}{\sum\limits_{k = 48}^{63}{{dct}\lbrack k\rbrack}},$and wherein dct[0:63] is the array of DCT coefficients.
 10. The computersystem of claim 6, wherein the processing system is further instructedby the software to: scale the array of DCT coefficients by a weightfactor contained in a weight array.
 11. The computer system of claim 10,wherein the processing system is further instructed by the software to:calculate a scalar from the array of DTC coefficients; calculate alowScore from the array of DTC coefficients; and calculate a highScorefrom the array of DTC coefficients.
 12. The computer system of claim 11,wherein calculate a scalar uses the formula:${{scalar} = {\min\left( {16,{{\sum\limits_{k = 48}^{63}{{dct}\lbrack k\rbrack}} + 2}} \right)}};$wherein calculate a lowScore uses the formula:${{lowScore} = {\left( {\sum\limits_{k = 1}^{5}\left\lbrack \frac{{{dct}\lbrack k\rbrack}*{{weight}\lbrack k\rbrack}}{scalar} \right\rbrack} \right)*{scalar}}};$wherein calculate a highScore uses the formula:${{highScore} = {\left( {\sum\limits_{k = 6}^{63}\left\lbrack \frac{{{dct}\lbrack k\rbrack}*{{weight}\lbrack k\rbrack}}{scalar} \right\rbrack} \right)*{scalar}}};$and wherein dct[0:63] is the array of DCT coefficients, and weight[0:63]is the weight array.
 13. The computer system of claim 11, wherein theprocessing system is further instructed by the software to: classify theblock as a plain block if lowScore is less than a plain threshold. 14.The computer system of claim 11, wherein the processing system isfurther instructed by the software to: classify the block as an unsharpblock if lowScore is less than highScore.
 15. The computer system ofclaim 11, wherein the processing system is further instructed by thesoftware to: classify the block as a sharp block if: lowScore is greaterthan or equal to highScore, lowScore is greater than or equal to a plainthreshold, the dark value is greater than or equal to a dark threshold,and the noise value is greater than or equal to a noise threshold. 16.The computer system of claim 1, wherein the processing system is furtherinstructed by the software to: mask the video frame.
 17. Anon-transitory computer-readable medium of instructions for triggeringan out of focus alert in a computer system, the instructions comprising:receiving a video frame; biasing the luminance of the video frame;partitioning the video frame into a plurality of blocks; calculating anarray of discrete cosine transformation (DCT) coefficients for at leastone of the plurality of blocks using a DCT; generating blockclassifications by classifying at least one block of the at least one ofthe plurality of blocks as noisy based on the array of DCT coefficientsfor that block; calculating a focus level of the video frame based atleast in part on the block classifications; and triggering an out offocus alert if the focus level meets a focus criteria.
 18. Thenon-transitory computer-readable medium of instructions of claim 17,wherein each block is classified as one block type from the group ofblock types consisting of: dark, noisy, plain, unsharp, or sharp. 19.The non-transitory computer-readable medium of instructions of claim 17,wherein the focus level is calculated by dividing the number of sharpblocks by the sum of the number of unsharp blocks and sharp blocks. 20.The non-transitory computer-readable medium of instructions of claim 17,wherein the focus criteria is a focus threshold.